bistaumanga Goto Github PK

apricot

apricot implements submodular selection for the purpose of selecting subsets of massive data sets to train machine learning models quickly.

bistaumanga.github.com

my website and blog

cmlab

website source for the computational media lab

compsumm-applicability

Applicability of comparative summarization

cs231n

datasci_course_materials

Public repository for course materials for the Spring 2013 session of Introduction to Data Science, an online coursera course.

dip_algorithms

A simple photo editor to demonstrate DIP Algorithms using python

exdata_plotting1

Plotting Assignment 1 for Exploratory Data Analysis

exdata_plotting2

Exploratory data analysis, assignment 2

icsisumm

Automatically exported from code.google.com/p/icsisumm

kaggle_digit

mmd-critic

mooc-setup

Information for setting up for the Spark MOOC

multi-document-summarization

Neural Network based MDS

numerical_methods

Implementation of Numerical methods Algorithms

pygsp

Graph Signal Processing in Python

pyml

MAchine Learning Algorithms from Professor Andrew Ng (Coursera, machine Learning online class) implemented in Python with numpy for vectorization

pyrouge

A Python wrapper for the ROUGE summarization evaluation package

pyvis

Python package for creating and visualizing interactive network graphs.

visual-semantic-embedding

Implementation of the image-sentence embedding method described in "Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models"